A state of the science review of wildfire-specific fine particulate matter data sources, methods, and models

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From the 33 studies included, three main estimation approaches emerged: chemical extraction, thresholding, and integration of satellite and fire-specific data (e.g., smoke plumes and fire perimeters). Most studies combined ground-based monitor data, satellite-derived aerosol optical depth, and explanatory data like meteorology and land use. The three public datasets indicated that in California, wildfire-specific PM2.5 contributed 11.2%-36.9% of total PM2.5 in 2010 and 13.7%-21.2% in 2018 with stronger agreement in 2018. Correlations were stronger in Modoc County (no monitors) (0.44-0.51 in 2010; 0.79-0.88 in 2018) than in Los Angeles County (densely populated area, 20 EPA monitors, where correlations ranged from 0.19-0.21 in 2010 and 0.54-0.79 in 2018). Overall, the datasets estimating total PM2.5 were more consistent than wildfire-specific PM2.5 estimates.